| Title: | Floating Catchment Area (FCA) Methods to Calculate SpatialAccessibility |
| Version: | 0.1.0 |
| Description: | Perform various floating catchment area methods to calculate a spatial accessibility index (SPAI) for demand point data. The distance matrix used for weighting is normalized in a preprocessing step using common functions (gaussian, gravity, exponential or logistic). |
| License: | GPL (≥ 3) |
| URL: | https://egrueebler.github.io/fca/,https://github.com/egrueebler/fca/ |
| BugReports: | https://github.com/egrueebler/fca/issues/ |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.1.2 |
| Suggests: | covr, knitr, rmarkdown, testthat |
| Config/testthat/edition: | 3 |
| VignetteBuilder: | knitr |
| NeedsCompilation: | no |
| Packaged: | 2021-11-29 17:57:32 UTC; munterfi |
| Author: | Etienne Grueebler [aut, cre], Merlin Unterfinger [aut], Reto Joerg [ctb] |
| Maintainer: | Etienne Grueebler <package@etienne.app> |
| Repository: | CRAN |
| Date/Publication: | 2021-12-06 08:30:02 UTC |
Distance weight methods
Description
Distance weight methods
Usage
dist_normalize(D, d_max, imp_function, function_d_max = 0.01)Arguments
D | numeric matrix, distance or time values |
d_max | numeric, threshold for max distance |
imp_function | character, type of distance weights method |
function_d_max | numeric, condition for the result of the function(d_max) used to calculate beta (default = 0.01, is considered optimal for the Gaussian function) |
Value
matrix, normalized distance or time values
Examples
dist_normalize(matrix(10), 10, "gaussian")Two-Step Floating Catchment Area method
Description
Two-Step Floating Catchment Area method
Usage
spai_2sfca(p, s, W, step = 2)Arguments
p | numeric vector, number of population at origin locations |
s | numeric vector, capacity of services at supply locations |
W | numeric matrix, distance or time matrix |
step | numeric, number of the steps of the method to perform |
Value
data.frame, depending on selected step
Examples
p <- 1:4s <- 1:6W <- matrix(1:24, ncol = 4, nrow = 6)spai <- spai_2sfca(p, s, W, step = 2)Three-Step Floating Catchment Area method
Description
Three-Step Floating Catchment Area method
Usage
spai_3sfca(p, s, W, step = 3)Arguments
p | numeric vector, number of population at origin locations |
s | numeric vector, capacity of services at supply locations |
W | numeric matrix, distance or time matrix |
step | numeric, number of the steps of the method to perform |
Value
data.frame, depending on selected step
Examples
p <- 1:4s <- 1:6W <- matrix(1:24, ncol = 4, nrow = 6)spai <- spai_3sfca(p, s, W, step = 3)Modified-Huff-Three-Step Floating Catchment Area method
Description
Modified-Huff-Three-Step Floating Catchment Area method
Usage
spai_mh3sfca(p, s, W, step = 3)Arguments
p | numeric vector, number of population at origin locations |
s | numeric vector, capacity of services at supply locations |
W | numeric matrix, distance or time matrix |
step | numeric, number of the steps of the method to perform |
Value
data.frame, depending on selected step
Examples
p <- 1:4s <- 1:6W <- matrix(1:24, ncol = 4, nrow = 6)spai <- spai_mh3sfca(p, s, W, step = 3)